Automatic quality control for wavelet-based compression of volumetric medical images using distortion-constrained adaptive vector quantization

An efficient compression scheme for 4-D medical images using hierarchical vector quantization and motion compensation

This paper proposes an efficient compression scheme for compressing time-varying medical volumetric data. The scheme uses 3-D motion estimation to create a homogenous preprocessed data to be compressed by a 3-D image compression algorithm using hierarchical vector quantization. A new block distortion measure, called variance of residual (VOR), and three 3-D fast block matching algorithms are used to improve the motion estimation process in term of speed and data fidelity. The 3-D image compression process involves the application of two different encoding techniques based on the homogeneity of input data. Our method can achieve a higher fidelity and faster decompression time compared to other lossy compression methods producing similar compression ratios. The combination of 3-D motion estimation using VOR and hierarchical vector quantization contributes to the good performance.

Performance Evaluation of JPEG 2000 for Specialized Electronic Patient Record Exchanges

Distant diagnostic services require the exchange of medical images and medical data in the form of specialized patient records. Given that multiple images for one patient are often used by these services, considerable demands are placed on support applications implementation, because of the processing and transmission infrastructure limitations found on isolated rural areas. This work proposes to evaluate the performance of medical image compression for such constrained scenario, based on the JPEG 2000 compression standard, in order to improve distant diagnostic services usability. Separate groups of 1 to 15 high resolution gray scale and color cytology images of fixed dimensions were compressed in one file, applying different possible bitrates, tile size and code-block size, for six discrete wavelet decomposition levels. Experimental results show that the adjustment of these parameters, allows compressing the worst data load case (135 MB with moderate lossy compression) in around two minutes, on an average current PC.